Literature DB >> 18413308

Gene-load score of the renin-angiotensin-aldosterone system is associated with coronary heart disease in familial hypercholesterolaemia.

Jeroen B van der Net1, Jeroen van Etten, Mojgan Yazdanpanah, Geesje M Dallinga-Thie, John J P Kastelein, Joep C Defesche, Richard P Koopmans, Ewout W Steyerberg, Eric J G Sijbrands.   

Abstract

AIMS: Familial hypercholesterolaemia (FH) is characterized by premature coronary heart disease (CHD). However, the incidence of CHD varies considerably among FH patients. Genetic variation in the renin-angiotensin-aldosterone system (RAAS) and the adrenalin/noradrenalin system may be of importance in determining the CHD risk in FH, because of their involvement in CHD. We investigated the association between CHD risk and combined genetic variation in the RAAS and adrenalin/noradrenalin system. METHODS AND
RESULTS: In 2190 FH patients, we genotyped six RAAS polymorphisms and five adrenalin/noradrenalin polymorphisms. For each patient, we calculated two gene-load scores by counting the number of risk genotypes within each pathway. Four of the six RAAS polymorphisms and none of the polymorphisms in the adrenalin/noradrenalin system were significantly associated with CHD (P < 0.05). The RAAS gene-load score was significantly associated with CHD (P(linear trend) < 0.001): in patients with a gene-load score of 5 or 6, the CHD risk was 2.3 times as high as in patients with a score of 0 or 1. The gene-load score of the adrenalin/noradrenalin system was not associated with CHD.
CONCLUSION: Genetic variation in the RAAS contributes gene-dose dependently to CHD risk in patients with FH, whereas genetic variation in the adrenalin/noradrenalin system is not associated with CHD.

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Year:  2008        PMID: 18413308     DOI: 10.1093/eurheartj/ehn154

Source DB:  PubMed          Journal:  Eur Heart J        ISSN: 0195-668X            Impact factor:   29.983


  2 in total

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Authors:  Paul E Drawz; John R Sedor
Journal:  Semin Nephrol       Date:  2010-03       Impact factor: 5.299

2.  Genome-based prediction of common diseases: methodological considerations for future research.

Authors:  A Cecile Jw Janssens; Cornelia M van Duijn
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  2 in total

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